[Retracted] Deep Unsupervised Hashing for Large-Scale Cross-Modal Retrieval Using Knowledge Distillation Model

Figure 1

The proposed SAKDH framework consists of two modules: unsupervised teacher model (a) and supervised student model (b). The teacher model is trained in an unsupervised way. By distilling the knowledge from the teacher model, the similarity matrix (soft similarity) is established, and it is used to supervise the student model. The teacher model adopted an unsupervised semantic alignment hashing method, and the student model adopts the joint loss of pairwise and triplet; these loss functions apply not only to intermodal, but also to intramodal.